Tutorials#

In this tutorial, you will learn how to run the Multimodal Data Visualization Microservice in Edge Video Analytics Microservice mode to visualize inference data from an Edge Video Analytics Microservice pipeline in Grafana* dashboard.

Time to Complete#

45 minutes

Learning Objectives#

These tutorials show how to use the Multimodal Data Visualization Microservice.
- Run Multimodal Data Visualization Microservice without Intel(R) Edge Insights System mode
- Run Multimodal Data Visualization Microservice in Intel(R) Edge Insights System mode

Tutorial 1: Run Multimodal Data Visualization Microservice without Intel(R) Edge Insights System mode#

Step 1:Run the Service#

The consolidated docker-compose.yml file present in the Visualizer dir for running the required services for this mode.
Run the application

  cd <Work-Dir>/Visualizer
  docker compose up -d

Note: For more details, refer to Run the Edge Video Analytics Microservice.

Step 2: Log into Grafana* Dashboard#

Open a web browser and go to http://localhost:3000 to access the Grafana dashboard.
Log into the dashboard using the user name and password mentioned in build/.env.

Step 3: Navigate the Grafana Dashboard to View the Data#

Return to the browser. On the Home Dashboard page, on the left corner, click the Dashboards icon.
Click the Manage Dashboards tab to view the list of all the preconfigured dashboards.
Select Video Analytics Dashboard to view the data from the Edge Video Analytics Microservice.
Refresh the Grafana dashboard to see the inference data and video stream from the Edge Video Analytics Microservice pipeline.

When a new pipeline is started in EVAM, you should see frame data being filling the current pipeline status and historical frame rate data boxes in the Grafana dashboard. To view the video stream, press the refresh button in the Stream data box - a new component will generate and autoconnect to the video source.

Note: Please refer EVAM Pipeline for more information on executing EVAM pipeline.

Step 4: Shutting Down the Service#

While in the build folder of the project, run the docker compose down -v command to shut down Docker containers of the Multimodal Data Visualization Microservice. You can also verify that the containers are no longer running, by running docker ps afterwards.

Stop the application
```
docker compose down -v
```

Tutorial 2: Run Multimodal Data Visualization Microservice in Intel(R) Edge Insights System mode#

Step 1:Run the Service#

Builder (builder.py) that exists inside IEdgeInsights/build directory, uses a yml file for building your application configuration. The config yml file consists of a list of services to include. You can mention the service name as the path relative to IEdgeInsights or full path to the service in the config yml file. To include only a certain number of services in the stack, you can add the -f or yml_file flag of builder.py.
```
python3 builder.py -f usecases/video-streaming-evam-datastore.yml
```

The above usecase yml file depicts the deployment which uses the Edge Video Analytics Microservice to ingest the video input from the camera. It publishes frames and meta-data to DataStore microservice and Visualizer microservice is used to visualize the video frames.

Run the application
```
./run.sh
```

Step 2: Verifying the Intel® Visualization Package Software by checking the visualization#

To import root cert in Visualizer, import cacert.pem from the build/Certificates/rootca/ directory to the browser certificates. Complete the following steps to import certificates:

In Chrome browser, go to Settings.
In Search settings, enter Manage certificates.
In Privacy and security, click Security.
On the Advanced section, click Manage certificates.
On the Certificates window, click the Trusted Root Certification Authorities tab.
Click Import.
On the Certificate Import Wizard, click Next.
Click Browse.
Go to the IEdgeInsights/build/Certificates/rootca/ directory.
Select the cacert.pem file, and provide the necessary permissions, if required.
Select all checkboxes and then, click Import.

Step 3: Log into Grafana* Dashboard#

Open a web browser and go to https://localhost:3000 to access the Grafana dashboard.
Log into the dashboard using the user name and password mentioned in build/.env.

Step 4: Navigate the Grafana Dashboard to View the Data#

Return to the browser. On the Home Dashboard page, on the left corner, click the Dashboards icon.
Click the Manage Dashboards tab to view the list of all the preconfigured dashboards.
Select EII Video and Time Series Dashboard to view the data from the Edge Video Analytics Microservice.
Refresh the Grafana dashboard to see the inference data and video stream from the Edge Video Analytics Microservice pipeline.

Step 5: Shutting Down the Service#

While in the build folder of the project, run the docker compose down -v command to shut down Docker containers of the Multimodal Data Visualization Microservice. You can also verify that the containers are no longer running, by running docker ps afterwards.

Stop the application
```
docker compose down -v
```

To Run Unit Test#

Bring up the MDVM containers by setting RUN_TESTS as “ON” and changing read_only as “false” in docker-compose.yml files of respective containers.
Exec into the containers and run the “run_test.sh” script i.e.

  docker exec -it multimodal-data-visualization-streaming bash 
  ./run_test.sh

or

  docker exec -it multimodal-data-visualization bash 
  ./run_test.sh

Summary#

In this tutorial, you learned how to:

Build the Docker images for the Multimodal Data Visualization Microservice.
Run the Multimodal Data Visualization Microservice in Edge Video Analytics Microservice mode.
How to submit a new object detection inference pipeline request to Edge Video Analytic Microservice’s HTTP API using CURL.
View the inference data from the Edge Video Analytics Microservice pipeline on the Grafana dashboard.
Shut down the Multimodal Data Visualization Microservice.
Ensure that the Multimodal Data Visualization Microservice has shut down cleanly.

Learn More#

Understand the components, services, architecture, and data flow in the Overview

Troubleshooting#

If streaming is not visible on the browser for “RUNNING” state pipelines, then make sure the HOST_IP environment variable is set in the .env file before running the containers.

   HOST_IP=<HOST_IP_ADDRESS>

Error Logs#

View the container logs using the command:

   docker logs -f <CONTAINER_NAME>

Known Issues#

Some network environments may prevent communication with subscribable services
At runtime, if Edge Video Analytics Microservice container fails to publish the frames due to camera error, then the Visualizer would keep showing the last received frame in Visualizer Streaming OR Visualizer Grafana UI.